Palo Alto-based startup Credo AI announced today that its AI governance platform will now be available on the Databricks Data Intelligence Platform.
According to Credo AI, Databricks customers will be able easily track and manage AI risk and compliance at scale, leveraging data and evidence already stored in the Databricks Data Intelligence Platform, providing transparency about their AI systems throughout the development lifecycle.
Credo AI, which launched in 2020 and raised $12.8 million in Series A funding in May 2022, will integrate with Databricks’ MLFlow, which manages the machine learning development lifecycle, to automatically translate model metrics and metadata into Model Cards and other required governance artifacts like AI Impact Assessments.
This is particularly important at a moment when regulations like the EU AI Act are emerging, which will require model providers and downstream developers to self-assess the risk of their AI systems, perform conformity assessments, maintain auditable registries, and monitor performance in addition to meeting transparency obligations based on the a model’s risk category.
“We set out four years ago with the core focus that we are going to be this layer of governance which provides continuous accountability and oversight over your technical infrastructure,” Credo AI founder and CEO Navrina Singh told VentureBeat in an interview.
“I think the Databricks partnership is going to be significant, setting the tone for 2024 — this is an indication to enterprises that the layer of governance needs to understand context and business priorities,” she said. “Not only can you manage your own risk, but you can actually really put out safe, responsible products in the market.”
In a press release, Roger Murff, VP of technology partners at Databricks, said ”we’re excited to partner with Credo AI to bring AI policy intelligence to the Databricks Data Intelligence Platform.” As companies develop their AI strategies, he added, “they realize how critical governance is to ensure a safe, responsible and compliant adoption of AI at scale.”
Palo Alto-based startup Credo AI announced today that its AI governance platform will now be available on the Databricks Data Intelligence Platform.
According to Credo AI, Databricks customers will be able easily track and manage AI risk and compliance at scale, leveraging data and evidence already stored in the Databricks Data Intelligence Platform, providing transparency about their AI systems throughout the development lifecycle.
Credo AI, which launched in 2020 and raised $12.8 million in Series A funding in May 2022, will integrate with Databricks’ MLFlow, which manages the machine learning development lifecycle, to automatically translate model metrics and metadata into Model Cards and other required governance artifacts like AI Impact Assessments.
Regulations will require AI risk self-assessment
This is particularly important at a moment when regulations like the EU AI Act are emerging, which will require model providers and downstream developers to self-assess the risk of their AI systems, perform conformity assessments, maintain auditable registries, and monitor performance in addition to meeting transparency obligations based on the a model’s risk category.
“We set out four years ago with the core focus that we are going to be this layer of governance which provides continuous accountability and oversight over your technical infrastructure,” Credo AI founder and CEO Navrina Singh told VentureBeat in an interview.
Databricks integration provides context for proper AI governance
“I think the Databricks partnership is going to be significant, setting the tone for 2024 — this is an indication to enterprises that the layer of governance needs to understand context and business priorities,” she said. “Not only can you manage your own risk, but you can actually really put out safe, responsible products in the market.”
In a press release, Roger Murff, VP of technology partners at Databricks, said ”we’re excited to partner with Credo AI to bring AI policy intelligence to the Databricks Data Intelligence Platform.” As companies develop their AI strategies, he added, “they realize how critical governance is to ensure a safe, responsible and compliant adoption of AI at scale.”
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Author: Sharon Goldman
Source: Venturebeat
Reviewed By: Editorial Team
